Data Retrieval, Generally
Current data retrieval methods rely on identifying and retrieving one or more data records from an informational database by executing some form of sequence-based, alphanumeric search query for one or more particular data fields. In order to effectively identify a desired record, a sufficient number of forward-sequential, alphanumeric characters must be entered into a search query to perform an exact match and corresponding proper identification and retrieval of a desired data record. Typically, an exact match of an entire whole alphanumeric word or data field is required to ensure one hundred percent confidence that the retrieved record is, in fact, the desired record. An example of a successful, whole-word, forward-sequential search query would require a user to enter “JOHN” in a first name field and “SMITH” in a last name field to find the database record for JOHN SMITH in a database containing names.
Current art has improved somewhat upon the need for an exact, whole-word or field match by allowing data retrieval systems to retrieve records with only a partial, forward-sequential, alphanumeric match of one or more data fields. Using the JOHN SMITH example above, a user may type in one or more forward-sequential letters of the first name, such as “JO” and one or more forward-sequential letters of the last name, such as “SM” into a search query. As with the whole-word match query, all JOHN SMITH data records are retrieved. One particular advantage of this type of partial, forward-sequential query is to minimize the number of keystrokes a user may be required to enter when retrieving data records. A significant disadvantage of this type of partial, forward-sequential query is that all data records that begin with “JO” in the first name field and begin with “SM” in the last name field are retrieved. The data record for JOSEPH SMALL is just as likely to be retrieved as the record for JOHN SMITH. The confidence of correct record identification and retrieval can only be increased as more and more forward-sequential characters are added to the appropriate search fields. In addition to methods for formulating and executing a single search query, prior art also teaches methods and systems for sequencing or ordering multiple search queries. Current art teaches that the middle, or intervening characters between the first and last positional characters are integral to both an exact, whole-word matching process and to an increasing confidence of an exact, forward-sequential, partial-word matching process.
Directory Assistance
Today's Directory Assistance (DA) retrieval systems and architecture also follow a strict, forward-sequential, partial-word matching process in which only the first three characters of a search term are used to retrieve all listing that match these first three characters. This basic trigram format is relatively inefficient in that it retrieves numerous listings which have a great likelihood of having the same, or very similar, spellings. A directory assistance agent may spend considerable time and resources paging through screens of retrieved, matching records in an attempt to identify the correct requested listing. Additionally, current DA database architecture is well-defined and usually contains three fixed search fields, each with a fixed length of 12 characters. Separate databases are also used for business, Most Frequently Requested (‘MFR’), Residence and Federal, State and local governments. Today's basic architecture has remained essentially the same since the mid-1970s. As then, the theory and intuitive and seemingly most efficient approach was that the first character of the primary name search field was the most important search character, with the additions of the second and third sequence-based search characters being incrementally relevant in a diminishing manner. Additional characters after the initial three characters were considered completely ineffective for common trigrams like INDiana and INDianapolis.
The recent use of automatic voice recognition (‘AVR’) technology has achieved a limited increase in efficiency and productivity. However, speaker independent systems and the requirement to correctly interpret or translate the request from over 200 million customers and then search and retrieve the one exact match out of 200 million directory listings is extraordinarily difficult. The result is a very low percentage of calls ‘contained’ within the AVR system and a correspondingly high substitution or error rate. Successful AVR calls are typically limited to high volume, MFR business directory requests with virtually no residential requests being completed with speaker independent AVR technology.
Despite the incremental improvements in productivity made by AVR technology, a number of problems still exist. These problems fall under several broad categories. For example, powerful search characters within the search parameters have not been included in the search algorithms; agent workstation consoles have not been integrated with database architecture, search parameters or search algorithms; unique database characteristics and structure have not been recognized; the root problems have not been clearly identified, AVR capability has not been fully integrated into the total process, and the agents Subject Matter Expertise (‘SME’) of the database has not been utilized.
The present invention is directed to improving these and other aspects of informational database record identification and retrieval methods and systems.